Specification and prediction of net income using by generalized regression Neural Network (A case study)

Forecasting the future of mining activity is noted to be the most important purpose of decision makers. Net income is a particular parameter that plays significant role in gaining the attention of investors. It is demonstrated that by indicating key parameters affecting on the net income, prediction...

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Main Authors: Taboli, H., Paghaleh, M., Jahanshahi, A., Gholami, Raoof, Gholami, R.
Format: Journal Article
Published: 2011
Online Access:http://hdl.handle.net/20.500.11937/18294
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author Taboli, H.
Paghaleh, M.
Jahanshahi, A.
Gholami, Raoof
Gholami, R.
author_facet Taboli, H.
Paghaleh, M.
Jahanshahi, A.
Gholami, Raoof
Gholami, R.
author_sort Taboli, H.
building Curtin Institutional Repository
collection Online Access
description Forecasting the future of mining activity is noted to be the most important purpose of decision makers. Net income is a particular parameter that plays significant role in gaining the attention of investors. It is demonstrated that by indicating key parameters affecting on the net income, prediction of net income will be considerably successful. Thus, the aim of this paper is to use an artificial intelligence method named generalized regression neural network (GRNN) for prediction of net income by taking into consideration of discounted cash flow table and six important parameters namely number of competitor, sales volume, annual cost, supply and demand, tax rate and inflation rate. Considering the six expressed parameters and Jade mine, Iran as case study, GRNN has shown appropriate result in the both training and testing step. As a result, GRNN has introduced itself as a robust method in the wide variety application of regression tasks.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T07:25:09Z
publishDate 2011
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spelling curtin-20.500.11937-182942017-01-30T12:07:01Z Specification and prediction of net income using by generalized regression Neural Network (A case study) Taboli, H. Paghaleh, M. Jahanshahi, A. Gholami, Raoof Gholami, R. Forecasting the future of mining activity is noted to be the most important purpose of decision makers. Net income is a particular parameter that plays significant role in gaining the attention of investors. It is demonstrated that by indicating key parameters affecting on the net income, prediction of net income will be considerably successful. Thus, the aim of this paper is to use an artificial intelligence method named generalized regression neural network (GRNN) for prediction of net income by taking into consideration of discounted cash flow table and six important parameters namely number of competitor, sales volume, annual cost, supply and demand, tax rate and inflation rate. Considering the six expressed parameters and Jade mine, Iran as case study, GRNN has shown appropriate result in the both training and testing step. As a result, GRNN has introduced itself as a robust method in the wide variety application of regression tasks. 2011 Journal Article http://hdl.handle.net/20.500.11937/18294 restricted
spellingShingle Taboli, H.
Paghaleh, M.
Jahanshahi, A.
Gholami, Raoof
Gholami, R.
Specification and prediction of net income using by generalized regression Neural Network (A case study)
title Specification and prediction of net income using by generalized regression Neural Network (A case study)
title_full Specification and prediction of net income using by generalized regression Neural Network (A case study)
title_fullStr Specification and prediction of net income using by generalized regression Neural Network (A case study)
title_full_unstemmed Specification and prediction of net income using by generalized regression Neural Network (A case study)
title_short Specification and prediction of net income using by generalized regression Neural Network (A case study)
title_sort specification and prediction of net income using by generalized regression neural network (a case study)
url http://hdl.handle.net/20.500.11937/18294